Features at diagnosis of 324 patients with acromegaly did not change from 1981 to 2006: acromegaly remains under‐recognized and under‐diagnosed
Bibliographic record
Abstract
BACKGROUND: Traditionally, acromegaly evaded diagnosis until in its clinically obvious later stages when treatment is more difficult. Over the last 25 years diagnostic tests have improved, but whether clinical disease detection also improved was unknown, so we tested if disease severity at diagnosis had changed from 1981 to 2006. METHODS: Data on 324 consecutive acromegaly patients presenting from 1981 to 2006 at two New York City hospitals were collected by retrospective review (n = 324) and by interview (n = 200). The main complaint, acromegaly associated comorbidities, signs, symptoms, healthcare providers visited, preoperative GH and IGF-I levels and pituitary tumour size at diagnosis were compared in patients presenting in the earlier vs. later halves of the time period. RESULTS: Times from symptom onset to diagnosis were 5.9 year (early) vs. 5.2 year (late; P = NS). At diagnosis, 96% of early and late groups had facial feature changes and/or hand/foot enlargement. Comorbidities included hypertension 37% (early) vs. 36% (late), carpal tunnel syndrome (24%vs. 24%), sleep apnoea (13%vs. 29%; P < 0.01), osteoarthritis (25%vs. 23%) and diabetes mellitus (18%vs. 15%); each patient had 1.2 (early) vs. 1.3 (late; P = 0.53) comorbidities. Groups were similar in signs, symptoms, tumour size, GH and IGF-I. CONCLUSIONS: Clinical, biochemical and tumour size characteristics at diagnosis of acromegaly patients were unchanged from 1981 to 2006. Most patients still have marked manifestations of acromegaly at diagnosis, suggesting that acromegaly remains clinically under-recognized. Healthcare professionals should more commonly consider acromegaly, which can lead to earlier diagnosis and better treatment outcome.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".